Antonyms vs synonyms distinction is a core challenge in lexicon-semantic analysis and automated lexical resource construction. These pairs share a similar distributional context which makes it harder to distinguish them from each other. Leading research in this regard at007 tempts to capture the properties of the relation pairs, e.g., symmetry, transitivity, etc. How009 ever, the inability of existing research to appropriately model the relation-specific properties limits their end performance. In this paper, we propose GRE, i.e., Graph-based Relational Encoder that aims to capture and model the relation-specific properties of the antonyms and synonyms pairs in order to perform the classifi016 cation task in a performance-enhanced manner. Experimental evaluation using the benchmark datasets shows that GRE outperforms the existing research by a relative score of up to 1.8% in F1-measure.

Tactile sensors have emerged as a promising technology for object identification, offering a distinct approach compared to traditional visual-based recognition systems. By relying on touch to detect and analyze physical properties, tactile sensors provide a more accurate and intuitive means of recognizing objects. This study aims to showcase the advantages of utilizing tactile sensors for object recognition. Through the development of a model, we demonstrate the effectiveness of tactile sensors in accurately recognizing objects. Our model achieved a high level of accuracy on the test set and successfully predicted the class label of sample images. Furthermore, this study highlights the potential of DIGIT tactile sensor 2D images for enhancing object recognition. Future explorations in this area aim to unlock this potential, paving the way for advancements in tactile-based perception systems.

To investigate the behaivor of SAMs on Au(111) at 150K using scanning tunneling microscopy.

Microneedle (MN) applications in healthcare vary widely, from transdermal drug and vaccine delivery to extraction of skin interstitial fluid (ISF). MNs are non-invasive due to their small size and design. They consist of tiny needle tips that penetrate the outermost layer of the skin without causing significant pain or damage. They vary in geometry (pyramidic, conical) typically having a height range of 50-900?m, and can be categorized into solid, hollow, and porous MNs. Herein, we developed a 3x3 solid MN array coated with a layer of hydrogel matrix for extraction of ISF due to their biocompatibility, water absorption and swelling behavioral properties. We experimented with different ratios of alginate to cross-linker to determine the optimal hydrogel that has the highest absorption volume and tested the mechanical strength of the MNs to ensure their capability of penetrating through skin. Results show that a ratio of 5:1 has high absorption properties, and a solid MN has an average fracture force of 0.1967 N.